The article explores the evolution of integrating Large Language Models (LLMs) with external data, introducing the Model Context Protocol (MCP). It compares MCP with traditional "Tools" (Function Calling), highlighting their fundamental differences and its potential to solve issues like vendor lock-in and fragmentation in AI development.
The future of AI agent ecosystems in 2026 will rely on standardized tool_use and function_calling protocols, with the Model Context Protocol (MCP) driving agent discovery and deployment. Transactions in these marketplaces will leverage x402 HTTP headers and USDC stablecoins on the Base chain for instant, low-cost settlements.
This tutorial explains how to use Claude's tool use (function calling) feature in Node.js, enabling the AI to call external functions and use their results for better answers. It covers the complete loop from defining tools to Claude executing them and integrating the output, with practical examples.
This content outlines three core LLM integration patterns: Function Calling, RAG, and Agent, providing guidance on how to choose the right one based on simplicity versus control tradeoffs, starting with Function Calling and escalating as needed.
The Model Context Protocol (MCP) enables AI models like Claude and Cursor to dynamically discover and invoke external tools. Modern MCP servers can also monetize through x402 and USDC on the Base chain for autonomous agent service payments.
This article explores tool use, or 'function calling,' which enables LLMs to interact with external systems and act as autonomous agents. It details essential patterns for defining, invoking, and chaining tool calls in production systems.
GLM-4 is a Chinese-English bilingual AI model from Tsinghua University / Zhipu AI, optimized from the ground up for both languages, unlike most English-centric models. It features a Mixture of Experts architecture for fast inference, long context up to 128K tokens, and a focus on function calling and agent workflows.
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This content explains how to leverage Claude's tool use (function calling) API to develop reliable AI agents suitable for production environments. It highlights the distinction from basic chatbots and includes a code example for defining tools.